Fix possible crash in scale-invariant error calculation
The logic for the scale-invariant calculation was quite complex
in the existing code, and depended on some tricky chains of logical
dependence between scale-invariant errors and general errors.
This change firstly eliminates unnecessary nesting by pulling the
scale-invariant error calculation out of the loop – the full calculation
only occurs once per computeAtomFields call, within its own loop.
Secondly, instead of crashing under certain conditions when the
scale-invariant error count is zero, this changes the code to simply not
compute the error in this case. (The complex chain of logic I had
followed to initially add the fatal crash turned out to be fallacious.)
Finally, this adds a testcase that fails without the changes to the
MetricsManager implementation (see ag/26418604). This added testcase
represents skipped/dropped input events, or an input interval greater
than the prediction interval.
Test: atest frameworks/native/libs/input/tests/MotionPredictorMetricsManager_test.cpp
Test: the above test fails without the changes to MotionPredictionMetricsManager.cpp
Test: `statsd_testdrive 718`, then draw with stylus → reported metrics are reasonable
Bug: 325711945
Change-Id: Ic56c0f0c810ec1b85b1906e16a8640824187d1fb
diff --git a/libs/input/MotionPredictorMetricsManager.cpp b/libs/input/MotionPredictorMetricsManager.cpp
index 0412d08..6872af2 100644
--- a/libs/input/MotionPredictorMetricsManager.cpp
+++ b/libs/input/MotionPredictorMetricsManager.cpp
@@ -113,7 +113,12 @@
// Adds new predictions to mRecentPredictions and maintains the invariant that elements are
// sorted in ascending order of targetTimestamp.
void MotionPredictorMetricsManager::onPredict(const MotionEvent& predictionEvent) {
- for (size_t i = 0; i < predictionEvent.getHistorySize() + 1; ++i) {
+ const size_t numPredictions = predictionEvent.getHistorySize() + 1;
+ if (numPredictions > mMaxNumPredictions) {
+ LOG(WARNING) << "numPredictions (" << numPredictions << ") > mMaxNumPredictions ("
+ << mMaxNumPredictions << "). Ignoring extra predictions in metrics.";
+ }
+ for (size_t i = 0; (i < numPredictions) && (i < mMaxNumPredictions); ++i) {
// Convert MotionEvent to PredictionPoint.
const PointerCoords* coords =
predictionEvent.getHistoricalRawPointerCoords(/*pointerIndex=*/0, i);
@@ -325,42 +330,44 @@
mAtomFields[i].highVelocityOffTrajectoryRmse =
static_cast<int>(offTrajectoryRmse * 1000);
}
+ }
- // Scale-invariant errors: reported only for the last time bucket, where the values
- // represent an average across all time buckets.
- if (i + 1 == mMaxNumPredictions) {
- // Compute error averages.
- float alongTrajectoryRmseSum = 0;
- float offTrajectoryRmseSum = 0;
- for (size_t j = 0; j < mAggregatedMetrics.size(); ++j) {
- // If we have general errors (checked above), we should always also have
- // scale-invariant errors.
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantErrorsCount == 0,
- "mAggregatedMetrics[%zu].scaleInvariantErrorsCount is 0", j);
-
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse < 0,
- "mAggregatedMetrics[%zu].scaleInvariantAlongTrajectorySse = %f "
- "should not be negative",
- j, mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse);
- alongTrajectoryRmseSum +=
- std::sqrt(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse /
- mAggregatedMetrics[j].scaleInvariantErrorsCount);
-
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse < 0,
- "mAggregatedMetrics[%zu].scaleInvariantOffTrajectorySse = %f "
- "should not be negative",
- j, mAggregatedMetrics[j].scaleInvariantOffTrajectorySse);
- offTrajectoryRmseSum +=
- std::sqrt(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse /
- mAggregatedMetrics[j].scaleInvariantErrorsCount);
+ // Scale-invariant errors: the average scale-invariant error across all time buckets
+ // is reported in the last time bucket.
+ {
+ // Compute error averages.
+ float alongTrajectoryRmseSum = 0;
+ float offTrajectoryRmseSum = 0;
+ int bucket_count = 0;
+ for (size_t j = 0; j < mAggregatedMetrics.size(); ++j) {
+ if (mAggregatedMetrics[j].scaleInvariantErrorsCount == 0) {
+ continue;
}
- const float averageAlongTrajectoryRmse =
- alongTrajectoryRmseSum / mAggregatedMetrics.size();
+ LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse < 0,
+ "mAggregatedMetrics[%zu].scaleInvariantAlongTrajectorySse = %f "
+ "should not be negative",
+ j, mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse);
+ alongTrajectoryRmseSum +=
+ std::sqrt(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse /
+ mAggregatedMetrics[j].scaleInvariantErrorsCount);
+
+ LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse < 0,
+ "mAggregatedMetrics[%zu].scaleInvariantOffTrajectorySse = %f "
+ "should not be negative",
+ j, mAggregatedMetrics[j].scaleInvariantOffTrajectorySse);
+ offTrajectoryRmseSum += std::sqrt(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse /
+ mAggregatedMetrics[j].scaleInvariantErrorsCount);
+
+ ++bucket_count;
+ }
+
+ if (bucket_count > 0) {
+ const float averageAlongTrajectoryRmse = alongTrajectoryRmseSum / bucket_count;
mAtomFields.back().scaleInvariantAlongTrajectoryRmse =
static_cast<int>(averageAlongTrajectoryRmse * 1000);
- const float averageOffTrajectoryRmse = offTrajectoryRmseSum / mAggregatedMetrics.size();
+ const float averageOffTrajectoryRmse = offTrajectoryRmseSum / bucket_count;
mAtomFields.back().scaleInvariantOffTrajectoryRmse =
static_cast<int>(averageOffTrajectoryRmse * 1000);
}